Barcelona Innovation District

Innovation doesn't happen on its own. It takes the right mix of industries, companies, institutions, and physical space before new ideas can take hold and grow. Aretian built databases and analysis methods to identify those ingredients and design site-specific innovation ecosystems, spanning economic, social, demographic, educational, and geographic factors.

I built much of this framework at Aretian, and Barcelona is the project where it came together most completely. I designed how the separate analyses connect into a single workflow and wrote the code for the innovation analysis at its core, which became the foundation for the rest of the company's work.

The method works in three steps.

First, three analyses gather the information:

• Economic & Innovation Analysis: measures how innovative and competitive the economy is, based on the city's unique industry makeup and benchmarked against top-performing innovation districts worldwide.
• Research Analysis: maps published and patented work from universities to identify technology-transfer opportunities and feed new ventures through commercialization programs.
• Geographic Analysis: establishes design criteria for layout and organization that make the district an attractive place to work.

Second, those results define the innovation pipeline: a step-by-step process for turning new ideas into impactful companies. Each step specifies the researchers, startups, technology-transfer centers, mature companies, and site-design requirements the district needs to include, forming the programmatic brief for the project.

Third, we translate the brief into a design proposal tailored to the site: creating the spaces each industry, company, transfer center, amenity, and transit connection requires, and integrating the district into the existing city fabric.

The full process is shown in the Aretian Analytics Engine diagram.

The City of Barcelona hired Aretian to develop a new innovation district on the North Eastern side of town. The goal was to replace an existing industrial and warehouse neighborhood with a new development to host the most advanced businesses and industries to grow Barcelona's economic and innovation ecosystem.

While Barcelona has one of the most diverse product and innovative ecosystems in Europe, it was also running out of modern office and lab space to stay competitive. The new space would provide the infrastructure and environment to attract fast growing companies and provide jobs for its residents.

Aretian built the client a custom database which describes all critical metrics to help design the new development. This new database allowed us to evaluate each business's innovation output and competitive position, then design the new campus based on the model's recommendations.

The goal is to identify how complex the products your nation and cities export are. Products that are exported bring in a surplus of capital, and therefore grow the economy. Complex products are also correlated with greater economic growth because they typically have competitive businesses fighting for market share, integrated supply chains, and fair business practices supported by institutions. Examples of complex products include semiconductors and automobiles.

Nations that export simple products, such as agriculture and mining, tend to grow more slowly and develop less diversified institutions than those built on complex manufactured goods.

The Product Space of Barcelona shows a highly activated network of complex industries. Each colored node in the network graph represents one or more businesses in the city, and the links between them show closely related industries. Grey nodes are not present in Barcelona's economy, and therefore present an opportunity to be incorporated. In addition, each node has a measure of complexity: the more complex a product is, the greater the long-term economic growth will be.

We complete this process by running a Smart Specialization Analysis. The horizontal axis shows how close unactivated nodes are, and on the vertical axis, how complex they are. Industries that fall into the top right hand corner are the target industries: they are close to your existing economy and highly complex. Therefore the group of industries they represent are most correlated with economic growth.

Analysis of the product space allowed us to understand the macro relationships between industries. At a smaller scale it is important to be able to understand how innovative each business is within its industry. This allows us to measure how advanced the business community is and how it connects to the rest of the innovation economy.

Aretian created an industry classification system to assign each business to its innovation category:

The tags allow us to see what percentage of the economy contributes to which phase of the innovation pipeline. Mapping the distribution across a city reveals where the pipeline is strong and where it breaks down.

Based on the size and profitability of companies, it is possible to weigh each business in the product space to see how innovative it is according to three new variables: innovation intensity, performance, and impact, which describe how each business contributes to the levels of innovation in the economy.

These metrics help establish the benchmarks for how large the new innovation district needs to be to affect the broader economy. If a new district does not reach roughly 20,000 people working in innovative roles, then the local economy will not have enough employees to reach critical mass.

The researcher database records what academics produce in their university labs: papers, patents, and publications, visualized as network graphs showing how individual contributors and department groups collaborate. Each output is tagged by domain and linked to startup and industry databases through crosswalk tables. For each university around Barcelona, we mapped every researcher's total output across six categories: school, department, publications, first-author papers, co-authored papers, and patents. The six-category breakdown showed which departments were the most productive and surfaced a specific list of individuals who could anchor the new district's research programs.

When we aggregate the research data to the department level, the noise of individual graphs disappears and larger trends for dominant research fields emerge. This lets us see what departments are the most productive and which research groups tend to collaborate with one another.

By comparing all of the city's universities, it's possible to clearly see what fields they are dominant in. While the academic research is very strong in Europe, universities lack technology transfer programs and struggle to commercialize innovative work.

To bridge the gap, we matched the most promising research fields to local startups and mature industries, creating the connections necessary to develop the startup and technology transfer programs that support the innovation economy.

Aretian's research found that specific street layout patterns, building density thresholds, and high concentrations of civic and public amenities contribute to the success of innovation districts. Geospatial statistics of urban forms such as betweenness (how often a street acts as a shortcut between other places), street length, building orientation, and block size we correlated with neighborhoods that had highly productive businesses. By measuring the entire city, it's possible to see where design improvements would help better connect separated neighborhoods to provide greater economic opportunities.

I completed the code and the analysis for this urban form work, from the geospatial metrics through to the connectivity and accessibility maps that shaped the district's design.

Urban morphology describes the physical shape of a city: the geometry of its streets, blocks, and buildings. Topology, how each element connects to one another, treats the city as a network of relationships rather than just a map of shapes. Together they determine how easy it is to move through a neighborhood and how many different routes exist between any two points.

Entropy measures the degree of disorder in a street network; higher entropy indicates more varied spatial arrangements that support multiple movement patterns. Fractality, how well a layout stays connected at every scale, from the block to the city, captures whether a layout stays well-connected at every scale simultaneously. A highly fractal urban fabric supports walking, mixed uses, and dense economic activity, due to its highly connected street network. This connection provides residents with the greatest opportunity to access amenities.

The site lacks amenities because it is a warehouse district. The new design added restaurants, shops, and public space to connect the active neighborhoods on either side of the site. Accessibility metrics, such as Reach and Gravity, describe how many nearby amenities are accessible within a given walk distance, and show how well residents and workers can reach services, shops, and public transit.

The analysis of industries, companies, people, institutions, and urban form produced specific recommendations for how to design the new innovation district. The final recommendations were tailored to the site, based on the total land availability, building layout, and industry mix.

Each program sheet below details how the recommended lists of researchers, departments, startups, and mature companies can be organized into industrially themed neighborhoods anchored by technology transfer centers. Each district neighborhood is sized according to the employment requirements and work activity needs.

The site is broken down into five innovation zones. Each program sheet from the innovation pipeline maps to the buildings within the district and contains: the research departments that generate the core knowledge, the technology transfer programs that bridge research to market, the innovation centers that incubate early-stage ventures, and the mature companies and support services that anchor the zone and attract talent.

From the economic and research analyses, we identified five industry clusters that are close to Barcelona's existing economy, aligned with the city's strongest research departments, and complex enough to generate long-term economic growth:

Each cluster program sheet maps research fields to innovation centers and to the related companies and support services. The sheets also show how each zone connects to its neighbors: which shared amenities, streets, and programs span cluster boundaries to create the cross-disciplinary encounters that productive innovation districts depend on.

Beyond the analysis, I led the team that delivered the project on time and within budget. I also ran the client meetings throughout the engagement and presented the findings and final design to key stakeholders.